Triple
T3446650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anne-Elisabeth Honorine Aubert |
E72693
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Aubert |
E71764
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Aubert | Statement: [Anne-Elisabeth Honorine Aubert, familyName, Aubert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aubert Context triple: [Anne-Elisabeth Honorine Aubert, familyName, Aubert]
-
A.
Aubert
chosen
Aubert is a French given name and surname of Germanic origin, historically associated with medieval nobility and Christian saints.
-
B.
Thibault
Thibault is a surname most notably associated with Mike Thibault, a prominent American basketball coach in the WNBA.
-
C.
Ganthier
Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
-
D.
Antoine
Antoine is the given name of Antoine de la Mothe Cadillac, the French explorer and founder of Detroit.
-
E.
Firmin
Firmin is a French given name notably borne by Firmin Didot, a renowned printer, typefounder, and member of the influential Didot family in the history of typography.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ad85b05c848190b7a28ceec2bd7b74 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adba6efb188190b989fa4d6f28e16b |
completed | March 8, 2026, 6:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b360e32ba08190bcd2f3cbe963c443 |
completed | March 13, 2026, 12:57 a.m. |
Created at: March 8, 2026, 3:16 p.m.